Wim Verhaegen > Math-LP > Math::LP

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NAME ^

Math::LP - OO interface to linear programs

SYNOPSIS ^

    use Math::LP qw(:types);             # imports optimization types
    use Math::LP::Constraint qw(:types); # imports constraint types

    # make a new LP
    $lp = new Math::LP;

    # make the variables for the LP
    $x1 = new Math::LP::Variable(name => 'x1');
    $x2 = new Math::LP::Variable(name => 'x2');

    # maximize the objective function to x1 + 2 x2
    $obj_fn = make Math::LP::LinearCombination($x1,1.0,$x2,2.0);  
    $lp->maximize_for($obj_fn);

    # add the constraint x1 + x2 <= 2
    $constr = new Math::LP::Constraint(
        lhs  => make Math::LP::LinearCombination($x1,1.0,$x2,1.0),
        rhs  => 2.0,
        type => $LE,
    );
    $lp->add_constraint($constr);
 
    # solve the LP and print the results
    $lp->solve() or die "Could not solve the LP";
    print "Optimum = ", $obj_fn->{value}, "\n";
    print "x1 = ", $x1->{value}, "\n";
    print "x2 = ", $x1->{value}, "\n";
    print "slack = ", $constr->{slack}, "\n";

DESCRIPTION ^

The Math::LP package provides an object oriented interface to defining and solving mixed linear/integer programs. It uses the lp_solve library as the underlying solver. Please note that this is not a two way relation. An LP is defined using Math::LP, converted to an lp_solve data structure, and solved with lp_solve functions. It is not possible to grab an lp_solve structure somehow and convert it to a Math::LP object for manipulation and inspection. If you want to do that kind of stuff in Perl, use the Math::LP::Solve package instead.

That being said, the logical way of constructing an LP consists of

  1. Construct Math::LP::Variable objects, in the meanwhile marking integer variables
  2. Construct Math::LP::LinearCombination objects with the variables and use them as the objective function and constraints
  3. Solve the LP
  4. Fetch the variable values from the Math::LP::Variable objects, the slacks and dual values from the Math::LP::Constraint objects. and the row values (including the optimum) from the corresponding Math::LP::LinearCombination.

DATA FIELDS ^

solver_status

Holds the status of the last solve() call. Can be either $OPTIMAL, $MILP_FAIL, $INFEASIBLE, $UNBOUNDED, $FAILURE, $RUNNING, $FEAS_FOUND, $NO_FEAS_FOUND or $BREAK_BB.

variables

A ref to a hash with all the Math::LP::Variable objects used in the LP indexed on their name.

constraints

A ref to an array with all Math::LP::Constraint objects used in the LP.

objective_function

A Math::LP::LinearCombination object representing the objective function

type

The optimization type. Can be either $MAX or $MIN.

METHODS ^

new()

returns a new, empty LP

nr_rows()

returns the number of rows, i.e. the number of constraints in the LP

nr_cols()

returns the number of columns, i.e. the number of variables in the LP

add_variable($var)

registers the variable as belonging to the LP. The index field of the variable is set as a side effect. For this reason it is not allowed to use 1 variable in 2 LP objects.

add_constraint($constr)

adds a Math::LP::Constraint to the LP. The index field of the constraint is likewise set. It is thus also not allowed to use a single constraint in more than 1 LP. All variables present in the constraint are automatically registered.

set_objective_function($lincomb,$type)

sets the objective function of the LP, specified by the following parameters:

$lincomb

a Math::LP::LinearCombination forming the objective function. New variables in the linear combination are automatically added to the LP.

$type

the optimization type, either $MAX or $MIN

maximize_for($lincomb)

shortcut for set_objective_function($lincomb,$MAX)

minimize_for($lincomb)

shortcut for set_objective_function($lincomb,$MIN)

solve([$lag_solve])

Solves the LP, returns true if succeeded (i.e. the status value is $OPTIMAL), false otherwise. The status of the solver is available in the status field afterwards. The default is to solve using solve(). If however $lag_solve is specified and true, lag_solve() will be used.

optimum()

Returns the value of the objective function obtained by the solver.

SEE ALSO ^

More info on the packages used in Math::LP is found in Math::LP::Object, Math::LP::Variable and Math::LP::LinearCombination.

The underlying wrapper to the lp_solve library is documented in Math::LP::Solve. It is based on the lp_solve library written by Michel Berkelaar and adapted by Jeroen Dirks. Documentation on lp_solve is distributed with the source code, and can be downloaded at ftp://ftp.ics.ele.tue.nl/pub/lp_solve/

AUTHOR ^

Wim Verhaegen <wimv@cpan.org>

COPYRIGHT ^

Copyright(c) 2000-2001 Wim Verhaegen. All rights reserved. This program is free software; you can redistribute and/or modify it under the same terms as Perl itself.

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